Dedicated to the advancement of the chemical sciences

The Camille and Henry Dreyfus Foundation has announced that Xiaowei Zhuang, Howard Hughes Medical Institute Investigator and David B. Arnold Jr. Professor of Science, Harvard University, is the recipient of the 2023 Dreyfus Prize in the Chemical Sciences. The international biennial Prize, which includes a $250,000 award, is conferred this year in Imaging in the Chemical Sciences. A public award ceremony is planned to be held at Harvard later this year.

Zhuang receives this top honor for her pivotal contributions to Imaging in the Chemical Sciences. She is recognized for pioneering work to develop groundbreaking super-resolution imaging and genome-scale imaging methods and utilizing those methods to gain important new insights about biological molecules and systems. These methods and insights have had a widespread impact in the fields of chemistry, biology, neuroscience, and medicine.

H. Scott Walter, President of the Dreyfus Foundation, remarked, “The Dreyfus Foundation is proud to recognize the numerous accomplishments of Xiaowei Zhuang in the field of imaging in the chemical sciences with the Foundation’s highest honor – the Dreyfus Prize in the Chemical Sciences.”

A groundbreaking leader in the field of super-resolution microscopy, Zhuang invented STORM (stochastic optical reconstruction microscopy), one of the earliest and most widely used super-resolution imaging methods. Overcoming the historical limitation of imaging resolution due to light diffraction, she creatively employed photoswitchable dyes and single-molecule imaging to increase the resolution of light microscopy to more than 10-times better than the diffraction limit. This methodology has been a key tool in advancing the understanding of molecular structures in cells, with her original 2006 paper alone garnering more than 8,000 scientific citations.

More recently, Zhuang invented MERFISH (multiplexed error-robust fluorescence in situ hybridization), a powerful method that took imaging to the genome scale. The technique uses error-robust barcoding, combinatorial labeling, and sequential imaging to allow for the determination of the precise copy number and spatial distribution of thousands of RNA species in individual cells, enabling single-cell transcriptome imaging. Zhuang further extended MERFISH to enable 3D-genome imaging and epigenome imaging. MERFISH transformed the studies of gene regulation in cells and the molecular and cellular architecture of biological tissues.

Zhuang has also actively employed these new methodologies to derive new insights into areas such as the cell atlas of the brain, molecular structures in neurons, and 3D organization of the genome.

“Xiaowei Zhuang’s numerous contributions to the field of imaging, most notably her invention of the STORM and MERFISH methods, have had a widespread impact on the scientific enterprise in fields from chemistry to neuroscience,” stated Matthew Tirrell, Chair of the Dreyfus Foundation Scientific Affairs Committee and Dean of the Pritzker School of Molecular Engineering at The University of Chicago.

In addition to her roles as Howard Hughes Medical Institute Investigator and the David B. Arnold Professor of Science at Harvard University, Zhuang is the Director of the Center for Advanced Imaging at Harvard. She is a co-founder of the company Vizgen, which commercialized the MERFISH technology, and is on the editorial board for both Science and Cell.

Zhuang is a member of the National Academy of Sciences, the National Academy of Medicine, the American Academy of Arts and Sciences, and the American Philosophical Society, as well as a foreign member of the Chinese Academy of Sciences and the European Molecular Biology Organization. She is also a Fellow of the National Academy of Inventors. Her many awards and honors include the Henrich Wieland Prize, J. Allyn Taylor International Prize in Medicine, the Foundation of NIH Lurie Prize in Biomedical Sciences, the Vilcek Prize in Biomedical Science, the Pearl Meister Greengard Prize, the Breakthrough Prize in Life Sciences, the Heineken Prize for Biochemistry and Biophysics, the National Academy of Sciences Award for Scientific discovery, and the MacArthur Fellowship.

Zhuang stated, “I am deeply honored to receive the 2023 Dreyfus Prize in the Chemical Sciences. I would like to thank the Camille and Henry Dreyfus Foundation for being a leading supporter of the chemical sciences community for over 75 years.”

The Dreyfus Prize in the Chemical Sciences, initiated in 2009, is conferred in a specific area of chemistry each cycle. It is the highest honor of the Camille and Henry Dreyfus Foundation.

The Camille and Henry Dreyfus Foundation is pleased to announce the selection of 18 Camille Dreyfus Teacher-Scholars for 2023. These faculty are within the first five years of their academic careers, have each created an outstanding independent body of scholarship, and are deeply committed to education. Each Camille Dreyfus Teacher-Scholar receives an unrestricted research grant of $100,000.

Vinayak Agarwal, Georgia Institute of Technology
Marine Biosynthetic Enzymology in Research and Education

Eszter Boros, Stony Brook University
Harnessing Coordination Chemistry of Non-Endogenous and Radioactive Metal Ions for Diagnosis and Therapy of Disease

Stephen Fried, Johns Hopkins University
How to Fold Every Protein – A Structural Proteomics Approach

Ariel Furst, Massachusetts Institute of Technology
Bio-Inspired Electron Transfer for Equitable Technologies

Grace Han, Brandeis University
Light-Responsive Organic Materials for a Sustainable Future

Chong Liu, University of Chicago
Designing Interfacial Ion Pathways for Critical Elements Separation

Jarad Mason, Harvard University
Manipulating Phase Transitions and Porosity in Metal-Organic Materials: From Solid Refrigerants to Porous Water

Phillip Milner, Cornell University
Simplifying Synthesis at the Interface of Organic and Materials Chemistry

Lea Nienhaus, Florida State University
Exploring Critical Parameters of Materials for High-Yield Solid-State Photon Upconversion

Jia Niu, Boston College
Precision Macromolecules for Sustainability and Biological Discoveries

Allie Obermeyer, Columbia University
Harnessing Protein Assembly for Living and Soft Materials

Lauren O’Connell, Stanford University
Predator-Prey Interactions as a Framework for Discovering New Chemical Toolkits

Zachariah Page, The University of Texas at Austin
Light as a Chemical Tool to Precisely Control Synthetic Soft Materials

Kimberly See, California Institute of Technology
Next-Generation Battery Chemistry

Christo Sevov, The Ohio State University
Battery-Inspired Strategies for Electrocatalytic Carbon-Carbon Bond Forming Reactions

Alexandra Velian, University of Washington
Molecular Approaches to Synthesize Single-Site Catalysts

Muzhou Wang, Northwestern University
New Methods Bringing Polymer Science into its Second Century

Wenjing Wang, University of Michigan
Molecular Sensors and Tools for Studying G-Protein-Coupled Receptor Signaling and Parkinson’s Diseas

Given the tremendous growth in machine learning research and funding opportunities, The Camille and Henry Dreyfus Foundation has decided to discontinue its award program for Machine Learning in the Chemical Sciences and Engineering.

Since the program was first announced in 2019, the Foundation has awarded over 20 grants totaling $2.4M to research investigators developing new approaches for machine learning in the chemical sciences.

“Originally conceived as a limited duration seeding program, the explosive growth of interest and work relating to machine learning has driven our decision to sunset the program at this time. We are pleased that machine learning has taken hold so strongly within the chemical sciences community,” said Dr. Matthew Tirrell, Chair of the Foundation’s Scientific Affairs Committee.

To-date, research funded by this work has resulted in three dozen publications and supported the training of more than 20 students and postdocs. Importantly, more than a dozen investigators have applied for follow-on funding from other sources, and several have already received such funding.  In many cases, this program also facilitated cross-functional and cross-departmental collaborations that might not otherwise have occurred.

Scott Walter, President of the Foundation commented: “The Board of Directors is grateful to all who have contributed to this program’s tremendous success. The Foundation maintains a strong interest in machine learning, and we will be looking at other ways to provide support. Importantly, we remain in close contact with the chemical sciences community so that the Foundation can identify other new and innovative areas of research where future seeding programs could also be of benefit.”

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